Number of significant figures to put in a table? Is there a well founded rule for the number of significant figures to publish? 
Here are some specific examples / questions:


*

*Is there any way to relate the number of significant figures to the coefficient of variation? For example, if the estimate is 12.3 and the CV is 50%, does that mean that the information represented by '.3' approaches zero?  

*If a confidence interval has a range of orders of magnitude, should they still have the same number of significant figures, e.g.:
12.3 (1.2, 123.4) vs 12 (1.2, 120) 

*Should the number of significant figures in an error estimate be the same or less than the number of significant figures in a mean?
 A: I doubt there's a universal rule so I'm not going to make any up.  I can share these thoughts and the reasons behind them:


*

*When summaries reflect the data themselves--max, min, order statistics, etc.--use the same number of significant figures used to record the data in the first place.  This provides a consistent representation throughout the document concerning the precision of the data.

*When summaries have higher precision than the data, write the values in a way that reflects that extra precision.  For instance, a mean of $n$ values has $\sqrt{n}$ times the precision of the individual values: roughly, include one extra significant figure for $3 \le n \le 30$, two for $30 \lt n \le 300$, etc.  (This is rounding on a log-10 scale, obviously.)
-Note that the CV does not provide useful information in this regard.
-Some estimates can be obtained with great precision.  They don't have to be rounded to match something else.  For instance, the mean of 1,000,000 integers might be 10.977 with a standard error of 0.00301.  My decision to write the mean to three decimal places (and 4-5 sig figs) was based on the order of magnitude of the SE, which indicates the last digit is partially reliable.  The decision to write the SE to three sig figs (five decimal places) is more arbitrary: two sig figs would work; one probably would not; four sig figs would also work and be consistent with the 4-5 sig figs in the mean; more than four sig figs would be overkill.  (One could estimate the standard error of the SE itself in terms of the fourth moment of the data, and use that to determine an appropriate amount of rounding, but most of us don't go to such trouble...)

*Signal the reader when you are doing substantial rounding.  Be especially careful when the report is discussing the statistical test itself.  The reason is that people may use your work to check their own calculations.  Sometimes even a slight difference can reveal an error.  You don't want to cause trouble because you rounded 123 to 120 and someone else, checking the work, obtains 123 and suspects one of you has erred.

*Be consistent.  You might lose some readers if you list a value as 123 at one point and later reference it as 120.

*Don't be ridiculous.  (I automatically suspect incompetence when I encounter reports that give statistical results to 15 sig figs when the data have only two sig figs, for instance.)
A: I'd suggest 12 (1.2, 123.4). Omit the .3 since it's nearly meaningless, but many people when they see (1.2, 120) will assume that the last '0' in 120 is significant.
